Prediction of driving behaviors in intersections based on a supervised dimension reduction considering locality.
Takatomi KuboRyunosuke HamadaZujie ZhangKazushi IkedaTakashi BandoKentarou HitomiMasumi EgawaPublished in: ITSC (2014)
Keyphrases
- dimension reduction
- feature selection
- unsupervised learning
- principal component analysis
- feature extraction
- high dimensional
- high dimensional problems
- data mining and machine learning
- low dimensional
- manifold learning
- variable selection
- linear discriminant analysis
- random projections
- high dimensional data analysis
- dimension reduction methods
- partial least squares
- singular value decomposition
- discriminative information
- preprocessing
- learning algorithm
- feature space
- high dimensional data
- dimensionality reduction
- machine learning
- high dimensionality
- cluster analysis
- semi supervised
- manifold embedding
- text classification
- supervised learning
- active learning
- data analysis